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66, 283291, https://doi.org/10.2307/1925829 (1984). 23. 17, 19) matrix, representing total indicator amount for each indicator. The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and conducted the research described herein under an approved Quality Assurance Project Plan (K-LRTD-0030017-QP-1-3). We examine these differences by indicator in a series of grouped charts comparing v2.0 and v1.2 impact coefficients (N matrix) by sector and indicator67. The first step is a relevance assessment to determine which of the 15 categories are relevant to the reporting organization. This bundle contains all of the available Global Emission Factors including: Global Electricity Factors, Global Homeworker Factors and Global Hotel Factors at a 10% discount. Collectively there are small decreases in ACID in most sectors. zenodo https://doi.org/10.5281/zenodo.6370618 (2021). Comparing rankings may also be used as another form of model validation that incorporates the demand vectors and the indicators as well as the model result matrices. L, the Leontief inverse, or the total requirements matrix, is obtained from A, using Eq. In Eq. Overview of GHG Protocol scopes and emissions across the value chain. Please click here to see any active alerts. With the direct impacts D and the total requirements L, the matrix N which contains the direct plus indirect impact coefficients can be calculated via Eq. As v1.2 represents the most recently previously peer-reviewed and published USEEIO model, but was built with a different set of data inputs and a different software procedure, comparing v2.0 results against v1.2 is a relevant means of performing model validation. As the matrix values are in producer price USD, the values in are commodity-specific producer:purchaser price ratios where a value of c,y is a ratio of year y USD producer price:year y USD purchaser price for commodity c. Margins tables provide values for transportation, t, wholesale, w, and retail, r, specific to each commodity consumed by industries, households or investors. EXIOBASE European Environment Agency Learn more on the project website. A similar approach is used to calculate the direct+indirect impacts x sector with the direct perspective as Hr but it uses includes the D direct impact matrix to characterize those flows as shown in Eq. The EEIO sector determines the region and sector-based factors which are used for estimating financed emissions. The consumption vector is defined in Eq. An Introduction to Environmentally-Extended Input-Output Analysis The GHG Emission Factors Hub provides factors for several scope 3 categories and indicates the calculation methods with which the factors align. The Use table is normalized by the industry output vector, x, to result in a commodity x industry direct requirements matrix. A lock (LockA locked padlock) or https:// means youve safely connected to the .gov website. MerckCorporate Responsibility Report Corn products shows a substantial increase in total CRHW relative to similar sectors. environmental pollution waste material air pollution water pollution, economic input-output data environmental release data resource use data. State level USDA CoA data are used to calculate fractions of land use by animal type, which are multiplied by state level MLU pasture and grazed land. What are emission factors? And where can I find them? EPA's GHG Emission Factors Hub provides factors for most scope 3 categories. The Use table intersection represents the consumption of the Waste management and remediation services commodity by the Waste management and remediation services industry itself. 35, is a vector of the column sums of the given H (see Eqs. US Environmental Protection Agency, Office of Research and Development, Washington, USA, General Dynamics Information Technology, Inc, Falls Church, VA, 22042, USA, Eastern Research Group, Lexington, MA, 02421, USA, You can also search for this author in It is the best value for money option. The disaggregation process is carried out by disaggregating distinct sections of the Use and Make tables. Natural Gas Gross Withdrawals and Production. This information is used to perform a default allocation of the expenses of the disaggregated waste management sectors along the Use table columns, except for the waste management sectors intersection and the value-added sectors. The result is available in the National Point Source Releases to Ground By Industry 2017 v1.1 dataset35. Then one can continue to derive the equivalent of L for domestic use, Ld from Ad, using Eq. The Use table rows represent the use of commodities by the industries in the IO table. This can be performed by subtracting the import matrix, Um from the Use matrix to estimate a domestic Use table, Ud, as in Eq. To assist in quantifying these emissions, EPA has developed a comprehensive set of supply chain emission factors covering all categories of goods and services in the US economy. Total flows or impacts associated with a given amount of final demand are calculated using two perspectives that produce the same overall flow or impact totals but associate the totals with different sectors. Results for these commodities should not be used for analytical purposes. . https://www.epa.gov/sites/production/files/2018-07/documents/nei2014v2_tsd_05jul2018.pdf (U.S. Environmental Protection Agency, 2018). The three zeroes at the end of the BEA code for Waste management and remediation services indicate that it is at the 3-digit NAICS level. Five categories are reported in year one and 12 in year five. The increase in impact intensity for Museums, historical sites, zoos and parks is explained by accounting for national parks in land use v2.0, whereas previously land for national parks was excluded. The USEEIO v2.0.1411 dataset is the primary data record, and includes the waste disaggregation data inputs, model components, result matrices, price adjustment matrices, and demand vectors, along with supporting metadata including sector, flow and indicator descriptions. Estimated use of water in the United States in 1995. U.S. EPA, 2020. Changes in selection of data sources and methodologies for compiling these into a standard format are described below. PDF Emission Factors for Greenhouse Gas Inventories B.Y. The technical model name for the model described here is USEEIO v2.0.1411 following the USEEIO versioning scheme as of model finalization9, but it is referred to throughout simply as v2.0. Emissions Factors 2021 - Data product - IEA Quarterly census of employment and wages 2017. https://www.bls.gov/cew/downloadable-data-files.htm (U.S. Bureau of Labor Statistics, 2020). Derivation of these demand vectors is described in depth in the Final Demand section, since these have not been previously described in USEEIO documentation. Meyer, D. E., Li, M. & Ingwersen, W. W. Analyzing economy-scale solid waste generation using the United States environmentally-extended input-output model. Young, B., Birney, C. & Ingwersen, W. National point source releases to water by industry 2017 v1.1. Domestic Proportion of the Impacts of US Consumption. Supply Chain Greenhouse Gas Emission Factors for US Industries and Commodities (No. U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1517571 (2020). The decline in impact intensity for Tobacco, cotton, sugarcane, peanuts, sugar beets, herbs and spices and other crops is attributed to correcting an error in the v1.2 calculation. This can be represented using Eq. Figure 1. 4. Ingwersen, W., Li, M. & Meyer, D. Commercial Waste National Totals by NAICS and US Satellite Tables for USEEIO. US Territories and Tribal Lands are not included. US Enviro nmental Protection Agency, Office . USEEIO v2.0, or referred to solely as v2.0, is the latest edition of the US Environmentally-Extended Input-Output (USEEIO) model for assessing a full suite of potential life cycle impacts of US. Open Source Softw. WRI's Sustainability Initiative was created to align the Institute's operations with its mission. Thus whatever is not explicitly allocated to 562211, Hazardous waste disposal, is assumed to go to Solid waste landfilling, 562112. The Make table intersection is allocated using the total Use table commodity output, adjusted for any manual allocations performed for the disaggregation of the Make table columns. 28 is a slightly modified form of the model result calculation using the direct perspective. This research was supported through USEPA contract HHSN316201200013W, Task Order EP-G16H-01256 with General Dynamics IT (GDIT) and contract EP-C-16-015, Task Order 68HERC19F0292 with Eastern Research Group (ERG). In v2.0, these data sources are used to allocate MLU land use categories to relevant sectors. Note:Emission factors are per unit of heat content using higher heating values (HHV). Allocation for this sector is described in the Make table intersection disaggregation section. Crop irrigation water withdrawal is initially calculated by determining water withdrawal for individual crops. AC-17-A-51 https://www.nass.usda.gov/Publications/AgCensus/2017/Full_Report/Volume_1,_Chapter_1_US/usv1.pdf (U.S. Department of Agriculture, 2017). in order to minimize inter-plant variability. The economic data base year for v2.0 is 2012, corresponding to the latest detailed IO tables10. figshare https://doi.org/10.6084/m9.figshare.17269211 (2021). Data are assigned to sectors based on facility-reported NAICS. In v1.2, national land use by animal type were calculated by importing and summing state level data for land in farms from USDA CoA. A selected comparable model result matrix (N) and sector rankings derived from full model LCIA calculations are appropriate for this validation and comparison, because they represent measures resulting from the combination of all model components both at the unit scale (impact per USD) and as a result of total US production and consumption. The production vector is defined in Eq. For instance, BEA code 1111A0 oilseed farming only connects to NAICS 5-digit codes 11111 soybean farming and 11112 oilseed (except soybean) farming in the table, but in fact 11111 and 11112 have single child codes 111110 soybean farming and 111120 oilseed (except soybean) farming, respectively, as well as shared parent codes 1111 oilseed and grain farming, 111 crop production, and 11 agriculture, forestry, fishing and hunting. It is a method that national statistical offices (NSOs) are beginning to adopt as a complement to other data produced in the System of Environmental-Economic Accounting (SEEA). Model validation and output writing are also performed in simple statements. However when this demand vector is applied to the model, output of these commodities is positive due to industry consumption, reflecting the commodity output totals. Once all the requirements are installed, the generation of v2.0 takes place in a single buildModel function to load the various data components and build the model. These factors were prepared using USEEIO models, which are a life cycle models of goods and services in the US economy. (Sheet CO2 KWH ELE & HEAT) CO 2 When making these improvements, it is recommended to focus first on categories with the largest impact on the organizations total GHG inventory. When imports are greater than final consumption and exports for a given commodity, the demand value will be negative. Report No. Sci. Although these emissions are not under the organizations control, the organization may be able to affect the activities that result in the emissions. Using these assumptions, the waste flows between the disaggregated waste management sectors are divided by the total waste shipped between 562 sectors (as indicated in the RCRAInfo data) to obtain a percent allocation value. However, the overall effects of any allocation scheme to the imports and exports sectors is fairly small, as they account for a small portion of total commodity use. These coefficients can then by multiplied by the cost of the purchase of interest to get the respective total flow or impact associated with that cost in purchasers price. CarbonSAVER: Scope3 Factors The EEIO sector also determines whether the project type is for construction or operation more broadly, and each has a very different greenhouse gas emissions profile. For example, Table 8 of the GHG Emission Factors Hub lists factors aligned with the distance-based method. The end products will not just benefit project partners in Georgia, but also include case studies and open-source resources for applying USEEIO in communities across the country. The data is built upon the US EPA's National Greenhouse Gas Industry Attribution Model. Themodified methodology results in significant sector disparities within agriculture, construction, retailing, finance, and household sectors. Additionally, QCEW publishes state and county employment data used in other sector attribution models used in USEEIO v2.0. CAS 44, 21262130, https://doi.org/10.1021/es903147k (2010). The intent of this detailed analysis is to provide information and recommendations on available opportunities to work with County vendors to improve environmental performance and advance the health and wellbeing of the residents of Alameda County and beyond., US Department of Energy Scope 3 emissions are the result of activities from assets not owned or controlled by the reporting organization, but that the organization indirectly affects in its value chain. Many organizations will improve the accuracy of scope 3 emissions over time and expand to include more categories as adequate data become available. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. The v1.2 model data used here for comparison were acquired from the USEEIO-API. 2. Equation24 is given below for the commodity form of the model. Increase in particulate matter emissions for livestock production. In some cases, environmental flows may appear in more than one satellite table if the associated sectors do not overlap. 34, where z is a vector of scores for each commodity, and h, calculated in Eq. https://doi.org/10.1038/s41597-022-01293-7, DOI: https://doi.org/10.1038/s41597-022-01293-7. This general decrease in v2.0 factors reflects the steady national decrease in SO2 emissions from 2011 to 201769. Improvements in modeling national totals of industry and environmental flows are described. USEEIO v2.0 described herein is a commodity model with the full breadth of US economic output split into 411 commodity categories.